Senior/Staff AI Research Scientist building post-training RL feedback loops and generative models that align frontier biological AI to high-throughput experimental measurements of folding, binding, and function. Requires PhD (or equivalent), hands-on training of models from scratch, and experience with diffusion/transformers/RL.
Principal AI Scientist at Polytope Bio (Astera) to co-direct development of reinforcement learning post-training methods that close the loop between frontier biological AI models and high-throughput experimental data. Requires PhD (or equivalent), hands-on training of large models from scratch, and deep RL expertise; ideal for researchers seeking scientific leadership and potential co-founding role.
Develop computational models of neural circuits and brain function. Requires Python, scientific computing libraries, and research experience in computational neuroscience. PhD or equivalent required.
Conducts fundamental research on data-efficient ML architectures, including bootstrapped program synthesis and self-synthesizing learning systems. Requires Master's in ML/math, PyTorch fluency, and research experience.
Develops bi-directional/recurrent architectures for hierarchical sensorimotor perception inspired by brain principles to advance AGI. Requires PhD-level expertise in deep learning frameworks like PyTorch/JAX, theoretical rigor, and passion for biological intelligence.
Conducts fundamental research on hierarchical RL agents, developing architectures for world modeling, planning, and ethologically constrained learning. Collaborates cross-functionally to translate brain-inspired principles into scalable AGI systems; requires PhD-level expertise in AI/ML and strong coding skills.
Conducts fundamental research on brain-inspired world models and AGI architectures, designing experiments on cognition, causal representations, and unsupervised learning. Collaborates with neuroscientists and engineers; requires PhD-level expertise in deep learning frameworks like PyTorch/JAX.
Conducts fundamental research on neuroscience-inspired energy-based models and hierarchical latent variable models for AGI. Designs experiments on cognition and collaborates cross-functionally to build scalable systems. Requires PhD-level expertise in deep learning and PyTorch/JAX.
Develops theories of intelligence grounded in neural network internal structures, focusing on belief geometries in LLMs and biological brains. Conducts experiments bridging mathematics, ML interpretability, and safety research; requires PhD-level quantitative depth and hands-on coding.
Senior/Staff AI Research Scientist building post-training RL feedback loops and generative models that align frontier biological AI to high-throughput experimental measurements of folding, binding, and function. Requires PhD (or equivalent), hands-on training of models from scratch, and experience with diffusion/transformers/RL.
Principal AI Scientist at Polytope Bio (Astera) to co-direct development of reinforcement learning post-training methods that close the loop between frontier biological AI models and high-throughput experimental data. Requires PhD (or equivalent), hands-on training of large models from scratch, and deep RL expertise; ideal for researchers seeking scientific leadership and potential co-founding role.
Develop computational models of neural circuits and brain function. Requires Python, scientific computing libraries, and research experience in computational neuroscience. PhD or equivalent required.
Conducts fundamental research on data-efficient ML architectures, including bootstrapped program synthesis and self-synthesizing learning systems. Requires Master's in ML/math, PyTorch fluency, and research experience.
Develops bi-directional/recurrent architectures for hierarchical sensorimotor perception inspired by brain principles to advance AGI. Requires PhD-level expertise in deep learning frameworks like PyTorch/JAX, theoretical rigor, and passion for biological intelligence.
Conducts fundamental research on hierarchical RL agents, developing architectures for world modeling, planning, and ethologically constrained learning. Collaborates cross-functionally to translate brain-inspired principles into scalable AGI systems; requires PhD-level expertise in AI/ML and strong coding skills.
Conducts fundamental research on brain-inspired world models and AGI architectures, designing experiments on cognition, causal representations, and unsupervised learning. Collaborates with neuroscientists and engineers; requires PhD-level expertise in deep learning frameworks like PyTorch/JAX.
Conducts fundamental research on neuroscience-inspired energy-based models and hierarchical latent variable models for AGI. Designs experiments on cognition and collaborates cross-functionally to build scalable systems. Requires PhD-level expertise in deep learning and PyTorch/JAX.
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Develops theories of intelligence grounded in neural network internal structures, focusing on belief geometries in LLMs and biological brains. Conducts experiments bridging mathematics, ML interpretability, and safety research; requires PhD-level quantitative depth and hands-on coding.